One of the main benefits of open-access journals is that they provide research articles freely and immediately to everyone online. This enhances their dissemination among researchers, allows them to showcase their work, and ensures that there are no barriers, such as cost, to knowledge, as anyone with internet access can reach the research from anywhere. However, the rapid growth of this model has also led to the emergence of questionable journals that exploit the publication fees paid by authors. These journals often promise rapid publication but lack a rigorous peer review process.
In a paper published in the journal “Science Advances,” researchers described how they trained artificial intelligence to work as a scientific investigator. They provided it with over 12,000 high-quality journals and about 2,500 low-quality or questionable publications. These journals were part of the Directory of Open Access Journals (DOAJ) but were removed for violating guidelines. The AI model learned to search for warning signs on journal websites and in their publications, such as lack of information about the editorial board, inaccurate website design, and low citation numbers.
The researchers then applied their trained model to a dataset containing 93,804 open-access journals. The researchers believe that further research can improve the features of the AI tool and help it keep up with the evolving tactics of questionable publishers. This will be an ongoing battle requiring sharp human insights and smarter AI systems. Humans and machines can collaborate to guide genuine researchers away from misleading journals and protect the integrity of scientific publishing worldwide.
